A novel precedence-based and heuristic approach for short-term scheduling of multipurpose batch plants

Many continuous-time formulations have been proposed during the last decades for short-term scheduling of multipurpose batch plants. Although these models establish advantages over discrete-time representations, they are still inefficient in solving moderate-size problems, such as maximization of profit in long horizon, and minimization of makespan. Unlike existing literature, this paper presents a new precedence-based mixed integer linear programming (MILP) formulation for short-term scheduling of multipurpose batch plants. In the new model, multipurpose batch plants are described with a modified state-task network (STN) approach, and binary variables express the assignments and sequences of batch processing and storing. To eliminate the drawback of precedence-based formulations which commonly include large numbers of batches, an iterative procedure is developed to determine the appropriate number of batch that leads to global optimal solution. Moreover, four heuristic rules are proposed to selectively prefix some binary variables to 0 or 1, thereby reducing the overall number of binary variables significantly. To evaluate model performance, our model and the best models reported in the literature (S&K model and I&F model) are utilized to solve several benchmark examples. The result comparison shows that our model is more effective to find better solution for complex problems when using heuristic rules. Note that our approach not only can handle unlimited intermediate storage efficiently as well as the I&F model, but also can solve scheduling problems in limited intermediate storage more quickly than the S&K model.     

A multi-objective optimisation model to integrating flexible process planning and scheduling based on hybrid multi-objective simulated annealing

Process planning and production scheduling play important roles in manufacturing systems. In this paper we present a mixed integer linear programming (MILP) scheduling model, that is to say a slot-based multi-objective multi-product, that readily accounts for sequence-dependent preparation times (transition and set up times or machine changeover time). The proposed scheduling model becomes computationally expensive to solve for long time horizons. The aim is to find a set of high-quality trade-off solutions. This is a combinatorial optimisation problem with substantially large solution space, suggesting that it is highly difficult to find the best solutions with the exact search method. To account for this, the hybrid multi-objective simulated annealing algorithm (MOHSA) is proposed by fully utilising the capability of the exploration search and fast convergence. Two numerical experiments have been performed to demonstrate the effectiveness and robustness of the proposed algorithm.     

A review: Energy recovery in batch processes

The implementation of batch processing has increased due to its intrinsic flexibility and adaptability. These are essential characteristics when it comes to producing high-value added materials such as agrochemicals, pharmaceuticals, specialty chemicals…the demand for which has grown in recent decades.Although industrial processes are highly diverse, a common feature to all is that they utilize fossil fuels as the energy source. The reliance on fossil fuels as a primary source of energy generates a negative impact on the environment. The implantation of renewable energies and efficient usage of energy has thus become crucial. Improving energy use could be achieved through advancements in plant machinery and the use of methodologies such as ‘process integration’.Process integration can be described as system oriented methods that could be used during the design and retrofit of industrial processes in order to obtain an optimal utilization of resources. The methods have traditionally focused on an efficient energy use, although recently process integration techniques cover other areas such as efficient use of raw materials, emission reduction and process operations. Energy integration tries to reach the optimization of heat, power, fuel and utilities.The consideration of energy integration complicates the process design and the generation of batch process design alternatives, so what is now required is the proposal and development of different approaches and methods oriented towards recovering energy in this kind of industrial process. Improving energy end-use efficiency will make it possible to reduce dependence on energy imports and bring about innovation and competitiveness.The aim of this work is report the main contributions that have been carried out in order to attain energy integration in batch processes, as well as different examples of applications that have shown the possibilities offered by the developed tools.     

Modeling the operation of hydrogen supply networks considering facility location

Hydrogen draws increasing attention as an alternative energy source. In order to provide hydrogen to various sectors such as industry, transportation on a global scale, how to produce and distribute it economically is an essential issue not to be missed. This study thereby addresses mathematical modeling of hydrogen supply networks. The proposed model is concerned with how much H₂ can be produced, where can be stored with the aim of maximizing the total net profit. Particularly the physical form of the hydrogen in the network is explicitly taken into account in terms of whether it is stored as a gas or a liquid. The applicability of the proposed model will be demonstrated by a case study of the Korean H₂ supply network with some remarks.     

Multi-week MILP scheduling for an ice cream processing facility

This paper presents a multi-week mixed integer linear programming (MILP) scheduling model for an ice cream processing facility. The ice cream processing is a typical complex food manufacturing process and a simplified version of this processing has been adapted to investigate scheduling problems in the literature. Most of these models only considered the production scheduling for a week. In this paper, multi-week production scheduling is considered. The problem has been implemented as an MILP model. The model has been tested on a set of cases from the literature, and its results were compared to the results of problems solved using hybrid MILP-heuristics methods in the literature. The inclusion of clean-up session, weekend break and semi-processed product from previous week were also assessed with two additional sets of experiments. The experiments result show that the proposed MILP is able to handle multi-week scheduling efficiently and effectively within a reasonable time limit.     

基于混合整数规划的智能网联车冲突区时序优化模型

智能网联车的大规模应用为交通冲突区域的优化与管理提供了新的机遇和挑战.为保证冲突区域车辆的汇入安全,提高冲突区域车流的运行效率,引入优化时间区间的概念,以车辆平均延误为优化目标,车辆通过冲突区域的最小安全时间间隔为约束条件,构建车辆进入冲突区域时序的混合整数线性规划模型.为研究不同流量状态对模型结果的影响,设计不同流量...     

The scheduling of maintenance. A resource-constraints mixed integer linear programming model

The scheduling of preventive maintenance is crucial in reliability and maintenance engineering. Hundreds of parts compose complex machines that require replacement and/or repairing. Maintenance involves the machine vendor (1), the machine user (2) and the service maintenance provider (3). The vendor and the maintenance service provider have to guarantee a high level of availability and productivity of the machines and maintain their down-time at a minimum even though they are installed worldwide and usually far from the vendor’s headquarters and/or the locations of the provider’s regional service offices. Moreover, many companies have great profits from maintenance and spare parts management.This study aims to illustrate an original mixed integer linear programming (MILP) model for the cost-based, reliability-based and resource-constraints scheduling of preventive maintenance actions. The model minimizes the total cost function made of spare parts contributions, the cost of the execution of the preventive actions and the cost of the additional repair activity in case of unplanned failure. The cost of the personnel of the producer and/or the maintenance service provider is also included. Finally, the paper presents a case study in a what-if environment demonstrating the effectiveness and the novelty of this study in real and complex applications.     

炼油企业生产计划和能量系统集成优化研究

炼油企业通常由生产过程和公用工程两个主要部分组成。将生产计划和公用工程集成优化,不仅获得真正的全局最优解,而且克服了传统生产计划人为制定生产过程与公用工程之间中间物流（各压力等级的蒸汽,瓦斯等）价格的缺陷,避免了蒸汽减温减压和放空,以及炼厂气放空的经济损失和环境破坏。首先采用IDEF0方法建立了生产计划与公用工程的功能模型,描述了两者之间的相互关系。接着建立了生产计划与公用工程集成的混合整数线性规划模型。模型描述了装置能耗不仅与加工量相关,而且与装置的生产方案相关,更真实地反映了生产过程与能量系统之间的定量关系。模型还在全厂范围内进行各压力等级蒸汽和燃料的平衡。最后,将建立的全厂集成优化模型应用于中国北方的某大型炼油厂,验证了模型的有效性。     

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Iron and steel works is not only major energy-consuming polluters but also a major source of pollutants. The boiler of power plant should be operated under the optimal scheme to meet the varying demand and power from process to reduce cost and save energy for petrochemical industry. A multi-period mixed-integer linear programming (MILP) optimization model for the boiler load with environmental costs was established and solved by using the improved particle swarm optimization (IPSO) algorithm. The results indicate: the fuel cost is 1015611 Yuan after optimization, about 77% in the whole running system. The total cost is less than the actual cost 50462. 864 Yuan approximately, decreased by about 3. 7%, saving a lot of cost. The feasibility and rationality of the model is solved based on the IPSO method, a better operational planning is attained to provide guidance quantificationally for the operating plan. Although considering environmental costs as part of the total cost increases the total business operating costs, to resolve the issue of environmental protection and coordinated and sustainable economic and social development has important significance.